The UK is in no way a leader in this field and the regional constabularies that make up law enforcement in this country have a patchwork record of using technology to uphold the law and detect crime more efficiently.

Much of this is to do with the federated way law enforcement is organised in the UK and the culture within the police forces in terms of attitude to the usefulness of technology.

Analytics is viewed more or less as dark art that has no place in day-to-day police work.

Retired Greater Manchester Police superintendant Keith Bentley, who was speaking at an IBM briefing on crime analytics, summed the situation up neatly by describing it as a choice between local policing and centrally-enforced standards on fighting crime.

There are still no consistent collaboration policies between police forces and with other agencies, such as local authorities. Initiatives which are lucky enough to find influential sponsors rarely flourish after that sponsor has moved on.

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More than this though, Bentley suggests that the resistance to direct-appointments at senior levels throughout UK policing has led to an aversion to novel ways of detection, in favour of protecting budgets allocated to maintaining staff levels.

All this could change though, with the election of new police commissioners next month. These people may not necessarily have come through the ranks and may be more willing to give 21st century methods a try. They will also be keen to implement processes that quickly bring crime rates under control. As elected officials, they are much more accountable to the local citizenry than career police officers, and will need to show voters rapid results to be sure of re-election.

According to Bentley and Ron Fellows, Global Lead, IBM Crime Information Solutions, there are a growing number of examples where the use of crime analytics has provided tangible benefits.

Fellows cited an IBM project with Hertfordshire police where collaboration and data integration led to a 10 per cent increase in crime detection. But this is the lowest level of using data to fight crime. Other forces he said, have gone further to use data to predict where crime is likely to occur.

For instance, Fellows worked with police in Tucson, Arizona to analyse historic crime data, integrated with geographical information to more effectively place officers where crime is likely to be committed. It resulted in a 60 per cent reduction in drug-related crime in one community over 12 months.

The system draws from a variety of data sources to match individuals to reported crimes with a degree of certainty.

We have been hearing for years how CIOs and senior IT professionals need to bury the hatchet with line of business managers and, instead of focusing on the latest bleeding-edge technology for its own sake, seek to better understand the overall strategic objectives of their organisations.